Associated Papers
Pathogenic variation in human DNA damage repair genes was originated from the evolutionary process of modern humans.
Li J et al.
Genes & Diseases, 2026
Prostate-Related Germline Variant Frequencies Detected in a Cohort of Men With Metastatic Prostate Cancer in Northern India.
Batra A et al.
Jco Precision Oncology, 2025
VarMeter2: An enhanced structure-based method for predicting pathogenic missense variants through Mahalanobis distance.
Ohno S et al.
Computational and Structural Biotechnology Journal, 2025
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
Pathogenic variants in human DNA damage repair genes mostly arose in recent human history.
Zhao B et al.
Bmc Cancer, 2024
Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes.
Lei H et al.
Human Genomics, 2024
Pathogenic variants in human DNA damage repair genes mostly arose after the latest human out-of-Africa migration.
He J et al.
Frontiers in Genetics, 2024
SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.
Canson DM et al.
Bioinformatics (oxford, England), 2023
Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification.
Tam B et al.
Iscience, 2023
Identification of SNPs in hMSH3/MSH6 interaction domain affecting the structure and function of MSH2 protein.
Singh S et al.
Biotechnology and Applied Biochemistry, 2022
Whole-exome Sequencing of Nigerian Prostate Tumors from the Prostate Cancer Transatlantic Consortium (CaPTC) Reveals DNA Repair Genes Associated with African Ancestry.
White JA et al.
Cancer Research Communications, 2022
Are transient protein-protein interactions more dispensable?
Ghadie MA et al.
Plos Computational Biology, 2022
Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants.
Loong L et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2022
Massively parallel functional testing of MSH2 missense variants conferring Lynch syndrome risk.
Jia X et al.
American Journal of Human Genetics, 2021
Mutation Edgotype Drives Fitness Effect in Human.
Ghadie M et al.
Frontiers in Bioinformatics, 2021
DNA Mismatch Repair Gene Variants in Sporadic Solid Cancers.
Caja F et al.
International Journal of Molecular Sciences, 2020
Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation.
Thompson BA et al.
Frontiers in Genetics, 2020
Novel Genetic Markers for Early Detection of Elevated Breast Cancer Risk in Women.
Wu B et al.
International Journal of Molecular Sciences, 2019
Immunogenomic profiles associated with response to neoadjuvant chemoradiotherapy in patients with rectal cancer.
Akiyoshi T et al.
The British Journal of Surgery, 2019
Estimating dispensable content in the human interactome.
Ghadie M et al.
Nature Communications, 2019
A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.
Shamsani J et al.
Bioinformatics (oxford, England), 2019
Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting.
Wright CF et al.
American Journal of Human Genetics, 2019
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations.
Nielsen SV et al.
Plos Genetics, 2017
Rare disruptive mutations and their contribution to the heritable risk of colorectal cancer.
Chubb D et al.
Nature Communications, 2016
Genetic diagnosis of high-penetrance susceptibility for colorectal cancer (CRC) is achievable for a high proportion of familial CRC by exome sequencing.
Chubb D et al.
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology, 2015
MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.
Mort M et al.
Genome Biology, 2014
Molecular and clinical characteristics of MSH6 germline variants detected in colorectal cancer patients.
Terui H et al.
Oncology Reports, 2013
Classification of mismatch repair gene missense variants with PON-MMR.
Ali H et al.
Human Mutation, 2012
Human Splicing Finder: an online bioinformatics tool to predict splicing signals.
Desmet FO et al.
Nucleic Acids Research, 2009
Functional characterization of pathogenic human MSH2 missense mutations in Saccharomyces cerevisiae.
Gammie AE et al.
Genetics, 2007
Systematic mRNA analysis for the effect of MLH1 and MSH2 missense and silent mutations on aberrant splicing.
Auclair J et al.
Human Mutation, 2006
Characterization of pathogenic human MSH2 missense mutations using yeast as a model system: a laboratory course in molecular biology.
Gammie AE et al.
Cell Biology Education, 2004
Systematic analysis of hMSH2 and hMLH1 in young colon cancer patients and controls.
Farrington SM et al.
American Journal of Human Genetics, 1998